Insecticidal Potential of α-Pinene and β-Caryophyllene against Myzus persicae and Their Impacts on Gene Expression

Myzus persicae(M.persicae)is now considered a threat to agricultural crops due to economic losses.Numerous synthetic insecticides applied every year against M.persicae,are reported to be unsafe for environment,humans,and beneficial insects.Furthermore,several species of Myzus have been found to develop resistance due to over application of these insecticides.Therefore,it is required to find some novel insecticide that would be safe for the environment as well as for humans.In the current study,two major pure constituentsα-pinene andβ-caryophyllene were evaluated for their insecticidal potential against M.persicae using a fumigant toxicity assay.Furthermore,impact ofα-pinene andβ-caryophyllene on expression of five different genes,e.g.,HSP 60,FPPS I,OSD,TOL and ANT responsible for reproduction,dispersion,and growth of M.persicae has also been investigated.To perform fumigant toxicity assay,five different concentrations(3.5,4,4.5,5 and 6μL L−1)ofα-pinene andβ-caryophyllene were prepared.Lethal concentration(LC)was calculated,and gene expression studies were executed through qRT PCR at LC30 ofα-pinene andβ-caryophyllene.Both constituents demonstrated excellent fumigant toxicity effects against M.persicae at all five concentrations.However,α-pinene shows significantly better results(98%)as compared toβ-caryophyllene(80%)after 72 h at 6μL L−1 of dose.The highest upregulation in expression was demonstrated at LC30 dose ofα-pinene in five in three out of five genes understudy(TOL,ANT,and FPPS I).Conversely,two genes HSP 60 and OSD demonstrated downregulation at LC30 dose ofβ-caryophyllene.Conclusively,our results highlighted the promising insecticidal potential of both compoundsα-pinene andβ-caryophylleneby interfering with the reproduction and development related processes in M.persicae,allowing us to recommend the phytoconstituents under investigation as an ecofriendly alternative to synthetic insecticides.

McSNAC:A software to approximate first-order signaling networks from mass cytometry data

Background:Mass cytometry(CyTOF)gives unprecedented opportunity to simultaneously measure up to 40 proteins in single cells,with a theoretical potential to reach 100 proteins.This high-dimensional single-cell information can be very useful in dissecting mechanisms of cellular activity.In particular,measuring abundances of signaling proteins like phospho-proteins can provide detailed information on the dynamics of single-cell signaling processes.However,computational analysis is required to reconstruct such networks with a mechanistic model.Methods:We propose our Mass cytometry Signaling Network Analysis Code(McSNAC),a new software capable of reconstructing signaling networks and estimating their kinetic parameters from CyTOF data.McSNAC approximates signaling networks as a network of first-order reactions between proteins.This assumption often breaks down as signaling reactions can involve binding and unbinding,enzymatic reactions,and other nonlinear constructions.Furthermore,McSNAC may be limited to approximating indirect interactions between protein species,as cytometry experiments are only able to assay a small fraction of protein species involved in signaling.Results:We carry out a series of in silico experiments here to show(1)McSNAC is capable of accurately estimating the ground-truth model in a scalable manner when given data originating from a first-order system;(2)McSNAC is capable of qualitatively predicting outcomes to perturbations of species abundances in simple second-order reaction models and in a complex in silico nonlinear signaling network in which some proteins are unmeasured.Conclusions:These findings demonstrate that McSNAC can be a valuable screening tool for generating models of signaling networks from time-stamped CyTOF data.